text string |
|---|
<reponame>Cristianobam/kappalib<gh_stars>0
import numpy as np
from ._summary import Correlation, TTest, Descriptive
from ._statistics import pooledVar
from scipy.stats import t, f, norm
__all__ = ['pooledVar', 'ttest', 'descriptives','correlation']
def ttest(x=None, y=None, alternative='two-sided', mu=0, data=None, ... |
from __future__ import print_function
import argparse
import os
import random
import torch
import torch.nn as nn
import torch.autograd as autograd
import torch.optim as optim
import torch.backends.cudnn as cudnn
from torch.autograd import Variable
import math
import util
import classifier
import classifier2
import sys... |
#
# This file is part of the statismo library.
#
# Author: <NAME> (<EMAIL>)
#
# Copyright (c) 2011 University of Basel
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# Redistributions of sour... |
<gh_stars>10-100
"""Commands to do statistics."""
import statistics
from plumeria.command import commands
from plumeria.util.command import string_filter
from plumeria.message.lists import parse_numeric_list
def format_output(n):
return "{:f}".format(n)
@commands.create('mean', category='Statistics')
@string_... |
<filename>plots/measures_of_goodness.py
from IPython import embed
import numpy as np
import scipy.stats as stats
import pandas as pd
import os
import sys
networks_path = os.path.abspath(os.path.join((os.path.abspath(__file__)), '../../networks'))
NNDB_path = os.path.abspath(os.path.join((os.path.abspath(__file__)), '.... |
# -*- coding: utf-8 -*-
"""Quantum_MNIST.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1WfmQHWMyJ6Dx1roE-Hm3RToyNHPuR_X5
[](https://colab.research.google.com/github.com/R... |
<reponame>alostbear/pymoo
import matplotlib.pyplot as plt
import numpy as np
from scipy.spatial.distance import pdist, squareform, cdist
from pymoo.model.problem import Problem
class TravelingSalesman(Problem):
def __init__(self, cities, **kwargs):
"""
A two-dimensional traveling salesman proble... |
"""
C++ Export
----------
This module provides all necessary functionality specify an ODE model and
generate executable C++ simulation code. The user generally won't have to
directly call any function from this module as this will be done by
:func:`amici.pysb_import.pysb2amici`,
:meth:`amici.sbml_import.SbmlImporter.sb... |
# -*- coding: utf-8 -*-
"""
Created on Sat Jun 23 16:26:58 2018
@author: manjotms10
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from keras.models import Sequential, Model
from keras.layers import Dense, Conv2D, Input, MaxPool2D, UpSampling2D, Concatenate, Conv2DTranspose
imp... |
"""Take 2 clouds of points, source and target, and morph
source on target using thin plate splines as a model.
The fitting minimizes the distance to the target surface.
"""
from vedo import *
import scipy.optimize as opt
import numpy as np
# np.random.seed(1)
class Morpher:
def __init__(self):
self.source ... |
<gh_stars>0
"""Modified version of Conway's Game of Life
Usually S[t] = CGOL(S[t-1]) where CGOL is the standard function of Conway's game of life,
and S is a binary matrix denoting if a cell is alive or dead.
Here it is modified to S[t] = Min(1, CGOL(S[t-1]) + L[t-1]) * (I - D[t-1])
where L and D are two matrices whi... |
import matplotlib
matplotlib.use('TkAgg') # This is needed for plotting through a CLI call
import matplotlib.pyplot as plt
import pandas as pd
import os
import numpy as np
import itertools
import seaborn as sns
from scipy.stats import ks_2samp
import argparse
import sys
# This function allows violinplots visualizati... |
<reponame>wrossmorrow/blendenpik
"""
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# DESCRIPTION # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #... |
<gh_stars>1-10
import sys
import os
import pandas as pd
import numpy as np
import scipy.interpolate
def interpolate_cm(bp, map_file):
""" TODO: summary docstring line.
Given a base position and recombination map file return the recombination
distance (in centimorgans, cM). Interpolate if required.
""... |
import numpy as np
from .simplemodel import SimpleForwardModel
from taurex.constants import PI
from taurex.util.emission import black_body
from taurex.core import derivedparam
import numba
@numba.jit(nopython=True, nogil=True,fastmath=True)
def contribute_ktau_emission(startK,endK,density_offset,sigma,density,path,wei... |
<filename>cpas_toolbox/datasets/nocs_dataset.py<gh_stars>1-10
"""Module providing dataset class for NOCS datasets (CAMERA / REAL)."""
import datetime
import imghdr
import json
from glob import glob
import os
import pickle
from shutil import copyfile
import time
from typing import TypedDict, Optional, List
import zipfil... |
<gh_stars>1-10
import argparse
import csv
from nltk.stem.wordnet import WordNetLemmatizer
from collections import defaultdict, Counter
import pandas as pd
from scipy.stats import zscore
import math
import warnings
from pandas.core.common import SettingWithCopyWarning
import pickle
from collections import Coun... |
<filename>rb/complexity/word/wd_avg_depth_hypernym_tree.py
from statistics import mean
from rb.complexity.complexity_index import ComplexityIndex
from rb.core.lang import Lang
from rb.core.text_element import TextElement
from rb.complexity.index_category import IndexCategory
from rb.complexity.measure_function import M... |
<reponame>valantiskon/Depression-Detection-using-ML<filename>SVM.py
import Twitter_Depression_Detection # Reads the input and the training sets
import numpy as np
from sklearn.model_selection import KFold
from sklearn import svm
from sklearn import naive_bayes
from sklearn.preprocessing import StandardScaler, MinM... |
<reponame>AndresdPM/GetGaia<gh_stars>1-10
#!/usr/bin/env python
from __future__ import print_function
import argparse
import sys
import os
import subprocess
import warnings
import numpy as np
import pandas as pd
pd.options.mode.chained_assignment = None
import matplotlib.pyplot as plt
from matplotlib.widgets import... |
from itertools import combinations
import numpy as np
from scipy import optimize
import scipy
import itertools
from numerik import lrpd, rref, ref, gauss_elimination
np.set_printoptions(linewidth=200)
# REF:
# MYERS, <NAME>.; MYERS, <NAME>.
# Numerical solution of chemical equilibria with simultaneous reactions.
# Th... |
"""
sip.py
Computes connectivity (KS-test or percentile scores) between a test similarity
gct and a background similarity gct. The default output is signed connectivity,
which means that the connectivity score is artifically made negative if the
median of the test distribution is less than the median of the background... |
<gh_stars>1-10
import spaceM
import matplotlib.pyplot as plt
import numpy as np
import tifffile as tif
import scipy.ndimage as scim
from skimage.morphology import ball
def scale(input):
"""Scale array between 0 and 1"""
return (input - np.min(input)) / ((np.max(input) - np.min(input)))
def contrast(arr, min, m... |
<filename>utils.py
# Copyright 2020 <NAME>
# Computer-assisted Applications in Medicine Group, Computer Vision Lab, ITET, ETH Zurich
import tensorflow as tf
import numpy as np
from scipy.spatial.transform import Rotation as R
def meshgrid2D(h, w):
x_coords = tf.linspace(0.0, w - 1, w)
x_coords = tf.reshape(x... |
<reponame>DaviGarba/netanalytics
import warnings
import numpy as np
import pandas as pd
from scipy.sparse import coo_matrix
from netanalytics.utils import _check_axis
def get_adjacency_csv(file):
data = pd.read_csv(file, index_col=0)
return data.values
def _params_check(G, filename, labels, axis):
... |
from __future__ import print_function
from __future__ import absolute_import
from __future__ import division
from math import sin
from math import cos
from math import pi
from compas.geometry.basic import scale_vector
from compas.geometry.basic import scale_vector_xy
from compas.geometry.basic import normalize_vector... |
<reponame>guoyingying432/lung-segmentation-by-unet-and-tensorflow
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 12 16:37:32 2019
@author: wjcongyu
"""
import cv2
import operator
import numpy as np
import SimpleITK as sitk
from skimage import measure
from scipy import ndimage
from scipy import signal
from... |
import numpy as np
from numpy import mean
import math
import random
import functools
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from scipy import optimize
from scipy.optimize import curve_fit
from fitEllipse import fit_ellipse
graphWidth = 800 # units are pixels
graphHeight = 600 # units ... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
#
# This file is part of the pyFDA project hosted at https://github.com/chipmuenk/pyfda
#
# Copyright © pyFDA Project Contributors
# Licensed under the terms of the MIT License
# (see file LICENSE in root directory for details)
"""
Widget for plotting impulse and general transien... |
<filename>causaldag/classes/gaussdag.py
# Author: <NAME>
"""
Base class for DAGs representing Gaussian distributions (i.e. linear SEMs with Gaussian noise).
"""
import operator as op
import itertools as itr
from typing import Any, Dict, Union, Set, Tuple, List
import numpy as np
from numpy import sqrt, diag
from numpy... |
from typing import Callable, Iterable, List, NamedTuple
import io
import os
import subprocess
import sys
import numpy as np
from scipy.io import wavfile
class Audio(NamedTuple("Audio", [("rate", int), ("data", np.ndarray)])):
"""A raw audio object with its rate as metadata.
Attribute:
rate: The sam... |
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
from scipy.constants import pi
from scipy.special import binom
import warnings
from .utilities import _initialize_figure, _format_axes
class _BasePipe(object):
"""
Template for pipe classes.
Pipe classes inherit from this class.
... |
import numpy as np
from scipy.optimize import fsolve
from numpy.random import uniform
from numpy import vectorize
#Gamma: 0.5625
#gamma: 2.0
#Aggragate Labor Good 0.9505050505050505
#Aggragate Labor Good 0.908080808080808
@vectorize
def U(c,n, Gam,gam):
if c<=0 or n<0 or n>1:
u = -np.inf
... |
<reponame>jsleb333/transboost
import numpy as np
import scipy.ndimage as sn
class AffineTransform:
"""
Computes the affine transformation from affine parameters and applies it to a matrix to transform, using its indices as coordinates.
"""
def __init__(self, rotation=0, scale=1, shear=0, translation=(... |
import sys
import cmath
# convert -1 + i decimal int to plural
num = sys.argv[1:]
if len(num) == 0:
print ("Converts a base -1 + 1j number, given in decimal")
print ("of hex, to the form a + bj, with a, b real.")
sys.exit()
num = eval(num[0])
r = 0
weight = 1
while num > 0:
if num & 1:
r = r + weight;
weight ... |
from nlp.core import get_encoder, MODELS, get_distance_func
import numpy as np
from scipy.spatial.distance import cosine
import math
gpt2_center = list(map(float, open("center.txt", 'r').read().strip('][').split(', ')))
def create_test(main_statement, comparisons):
def tests(distance_func, file_p):
# main_... |
<gh_stars>1-10
#
# This implementation is based on https://github.com/WXinlong/SOLO/blob/master/tools/test_ins_vis.py
#
import json
import numpy as np
import pycocotools.mask as mask_util
import mmcv
from scipy import ndimage
import cv2
from tqdm import tqdm
from config import dataset_meta
def vis(conf_threshol... |
import numpy as np
import scipy as sp
import qutip as qt
from pyqm import purity
from numpy.testing import assert_, assert_equal, assert_almost_equal
def test_purity():
"""
Test the purity function
"""
psi = qt.fock(3)
rho_test = qt.ket2dm(psi)
test_pure = purity(rho_test)
assert_equal(test... |
<reponame>aaronchantrill/jasper-client<gh_stars>1-10
import logging
import os
import requests
import sys
import scipy.io.wavfile as wav
from jasper import plugin
try:
from deepspeech.model import Model
deepspeech_available=True
except ImportError:
deepspeech_available=False
class DeepSpeechSTTPlugin(plugi... |
import numpy as np
import numpy.linalg as la
import numpy.random as npr
import scipy.linalg as sla
from functools import reduce
import matplotlib.pyplot as plt
def mdot(*args):
"""Multiple dot product."""
return reduce(np.dot, args)
def sympart(A):
"""Return the symmetric part of matrix A."""
return... |
"""Checks import order rule"""
# pylint: disable=unused-import,relative-import,wrong-import-order,using-constant-test
# pylint: disable=import-error
import six
import logging.config
import os.path
from astroid import are_exclusive
import logging # [ungrouped-imports]
import unused_import
try:
import os # [ungroup... |
import numpy as np
from scipy import optimize
# Adapted from the SciPy Cookbook
def calc_R(x,y, xc, yc):
""" calculate the distance of each 2D points from the center (xc, yc) """
return np.sqrt((x-xc)**2 + (y-yc)**2)
def f(c, x, y):
""" calculate the algebraic distance between the data points and the mea... |
<filename>skompiler/fromskast/sympy.py
"""
SKompiler: Generate Sympy expressions from SKAST.
"""
import numpy as np
import sympy as sp
from ..ast import IsElemwise, Mul
from ._common import ASTProcessor, is_, StandardOps, StandardArithmetics
def translate(node, dialect=None, true_argmax=True, assign_to='y', component... |
<filename>examples/molecules/datagen.py
import argparse
import numpy as np
import scipy.io as spio
from scipy.spatial import distance as spdist
import joblib
import lie_learn.spaces.S2 as S2
MAX_NUM_ATOMS_PER_MOLECULE = 23
NUM_ATOM_TYPES = 5
def get_raw_data(path):
""" load data from matlab file """
raw = s... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
#from choldate import cholupdate, choldowndate
import scipy.special as special
import scipy.constants as constants
import scipy.optimize as optimize
from .lda import LDA
class JLDA(LDA):
'''
Join Latent Dirichlet Allocation
'''
def __init... |
<gh_stars>10-100
import _init_paths
import cv2
from pymongo import MongoClient
import time
import operator
import numpy as np
import utils.zl_utils as zl
from nltk.stem import PorterStemmer, WordNetLemmatizer
from textblob import TextBlob as tb
from textblob_aptagger import PerceptronTagger
import nltk
from nltk.tag.... |
import numpy as np
from scipy import stats
X = int(input())
N = list(map(int, input().split()))
print(np.mean(N))
print(np.median(N))
print(stats.mode(N)[0][0])
|
<gh_stars>0
import scipy.stats
import numpy as np
def hypergeometric(binary_classification,feature_matrix):
X = feature_matrix
y = binary_classification
nF = feature_matrix.shape[1]
pvals = np.ones(nF) #p-values
M = feature_matrix.shape[0] #total number of objects
n = sum(y) #number in c... |
# -*- coding: utf-8 -*-
u"""SRW execution template.
:copyright: Copyright (c) 2015 RadiaSoft LLC. All Rights Reserved.
:license: http://www.apache.org/licenses/LICENSE-2.0.html
"""
from __future__ import absolute_import, division, print_function
from pykern import pkcompat
from pykern import pkio
from pykern.pkcollec... |
<filename>ProgettoLube/WebInspector/venv/Lib/site-packages/skimage/metrics/_contingency_table.py
import scipy.sparse as sparse
import numpy as np
__all__ = ['contingency_table']
def contingency_table(im_true, im_test, *, ignore_labels=(), normalize=False):
"""
Return the contingency table for all regions in ... |
# Copyright 2019 Xilinx Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
# Copyright 2019 British Broadcasting Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... |
<filename>kde_diffusion/kde2d.py
"""Kernel density estimation via diffusion for 2-dimensional data."""
__license__ = 'MIT'
########################################
# Dependencies #
########################################
from numpy import array, arange
from numpy import exp, sqrt, pi... |
import logging
import sys
from dataclasses import dataclass
from typing import TextIO, Tuple, cast
import scipy.stats
from .abstract import AbstractEvaluator
from .common import EvalResult, evaluate
ScoreResult = Tuple[float, float, float]
@dataclass
class WilcoxonEvaluator(AbstractEvaluator):
"""
Evaluato... |
<reponame>cqh6666/transfer_learning_code
import numpy as np
import scipy.io
import scipy.linalg
import sklearn.metrics
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score
from sklearn.svm import LinearSVC
from scipy.linalg import eig
class JDA:
'''
Implements Joint ... |
<filename>src/speaker_verification_lstm_model.py
"""
This file contains the LSTM Deep Learning NN model usage for speaker identification in a phone call.
An existing pre-trained model is loaded from configuration path and used to retrieve embedding from speach utterances.
"""
import tensorflow as tf
import numpy as np... |
<gh_stars>0
# import packages
import os
import cv2
import imutils
import argparse
import numpy as np
import time
from pyimagesearch.descriptors.histogram import Histogram
from sklearn.cluster import KMeans
from scipy.spatial import distance as dist
import sys
sys.path.append(os.path.abspath("."))
from games.camera.came... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 15 13:14:02 2021
@author: shrohanmohapatra
"""
from sympy import symbols, integrate, simplify
x, y = symbols('x y')
print(simplify(integrate(1/(1-x**2-y**2),(y,0,1-x))))
# Answer to the above
# sqrt(-1/(x**2 - 1))*(-log(sqrt(-1/(x**2 - 1))*(1 - x*... |
"""
*Function reads SLP and ENSO data from CESM control.
Years listed below are for leaf/bloom March 2012-CESM correlations.
Plots can create animations for SLP data*
"""
from control_SLP_datareader import SLP
import matplotlib.pyplot as plt
import numpy as np
from netCDF4 import Dataset
from mpl_toolkits.basemap im... |
## @ingroup Methods-Aerodynamics-Common-Fidelity_Zero-Drag
# compressibility_drag_wing.py
#
# Created: Dec 2013, SUAVE Team
# Modified: Nov 2016, <NAME>
# Apr 2020, <NAME>
# Apr 2020, <NAME>
# May 2021, <NAME>
# -------------------------------------------------------------------... |
<reponame>KorotkiyEugene/dsp_sdr_basic
import numpy as np
from common import create_harmonic, create_from_wav, usb_demod, usb_mod, plot_spectrum
from common import filt, interpolate, decimate, create_complex_exponent
import matplotlib.pyplot as plt
from scipy.io.wavfile import write as write_wav
CARRIER_FREQUENCY = ... |
<reponame>kungfuai/d3m-forecasting-research
from typing import Dict, List
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from pandas._libs.tslibs.timestamps import Timestamp
from statsmodels.tsa.vector_ar.var_model import VARResultsWrapper
from gluonts.evaluation import Evaluator
import scipy.s... |
import torch
import math
import numpy as np
import scipy.special
import torch.nn.functional as F
class BIMM1D(torch.nn.Module): #inherits from Module class
'''Arc model for material with n_phases'''
def __init__(self, n_phases):
super(BIMM1D, self).__init__() #initializes superclass, does set-up
... |
<reponame>qiaoxiaobin2018/mfcc_cnn
# coding=utf-8
import os
import time
import numpy as np
from keras import layers
import keras.backend as K
from keras.models import load_model
from scipy.spatial.distance import cdist, euclidean, cosine
from glob import glob
from tools import get_mfcc_1,calculate_eer,get_mfcc_2
import... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""Functions for simulating dog vision.
L and S response curves estimated from graph in
'Colour cues proved to be more informative for dogs than brightness'
<NAME>, <NAME>, <NAME>
Proc. R. Soc. B 2013 280 20131356; DOI: 10.1098/rspb.2013.1356.
Published 17 July 2013
using WebPlot... |
#!/usr/bin/python
import argparse
import nifgen
import numpy as np
from scipy import signal
import sys
import time
number_of_points = 256
def calculate_sinewave():
time = np.linspace(start=0, stop=10, num=number_of_points) # np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)
ampli... |
<filename>assets/code/GF.py
from PIL import Image
import numpy as np
import math
from scipy import signal
def boxfilter(n):
assert (n%2 != 0),"Dimension must be odd"
a = np.empty((n, n))
a.fill(1/(n*n))
return a
def gauss1d(sigma):
arr_length = 6*sigma
if arr_length % 2 == 0:
val = ((a... |
<reponame>amitkumarj441/QNET<gh_stars>10-100
from functools import partial
import pytest
from sympy import symbols, sqrt, exp, I, Rational, IndexedBase
from qnet import (
CircuitSymbol, CIdentity, CircuitZero, CPermutation, SeriesProduct,
Feedback, SeriesInverse, circuit_identity as cid, Beamsplitter,
Op... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Testing the STL arbit 3D volume simulation option in pyroomacoustics
Code is a slightly modified version of that on the Github repo
(https://github.com/LCAV/pyroomacoustics/blob/pypi-release/examples/room_from_stl.py)
"""
import matplotlib.pyplot as plt
import num... |
<filename>pylearn2/datasets/tests/test_sparse_dataset.py
"""
Unit tests for ../sparse_dataset.py
"""
import numpy as np
from pylearn2.datasets.sparse_dataset import SparseDataset
from pylearn2.train import Train
from pylearn2.models.model import Model
from pylearn2.space import VectorSpace
from pylearn2.termination_cr... |
<reponame>dimitra-maoutsa/DeterministicParticleFlowControl
# -*- coding: utf-8 -*-
"""
Created on Sun Dec 12 04:14:07 2021
@author: maout
"""
# optimal transport multidimensional reweighting
from pyemd import emd_with_flow
import numpy as np
from scipy.spatial.distance import pdist, squareform
__all__ = ["reweight... |
import numpy as np
import pandas as pd
from scipy.optimize import brentq
pd.set_option('mode.chained_assignment', None)
class Instrument:
def __init__(self, survey):
# General survey information
self.name = survey.instrument
# General survey observing/instrument information
self... |
# -*- encoding: utf-8 -*-
'''
@Author : lance
@Email : <EMAIL>
'''
from skimage import io,transform,exposure
import numpy as np
import os
imgpath="./data/test/C3F/C3F_blockId#32756.bmp"
img=io.imread(imgpath)
io.imshow(img)
print(type(img)) #显示类型
print(img.shape) #显示尺寸 #height/weight/channel
print(img.... |
<filename>mcmcplot/utilities.py<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 14 06:24:12 2018
@author: prmiles
"""
import numpy as np
from scipy import pi, sin, cos
import sys
import math
def check_settings(default_settings, user_settings=None):
'''
Check user settings ... |
import numpy as np
import scipy.stats as stats
import aesara
from aesara.tensor.basic import as_tensor_variable
from aesara.tensor.random.op import RandomVariable, default_shape_from_params
from aesara.tensor.random.utils import broadcast_params
try:
from pypolyagamma import PyPolyaGamma
except ImportError: # p... |
<reponame>ciholas/cuwb-monitor
# Ciholas, Inc. - www.ciholas.com
# Licensed under: creativecommons.org/licenses/by/4.0
# System libraries
import numpy as np
import sys
import time
from collections import deque
from math import sqrt, log10, pi, e
from scipy.signal import find_peaks_cwt
# Local libraries
from settings ... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
T=[0.9294117647,0.9294117647,0.9294117647,0.9295624333,0.9294117647,0.9294117647,0.9294117647,0.9295624333,0.9254966887,0.9042979943,0.9006354708,0.8895382817,0.8800471559,0.8740740741,0.8666865494,0.8578298768,0.8481357987,0.84813... |
<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This module implements an analytical along side with a numerical
solution for the quantum harmonic oscillator eigenstates and
eigenvalues. It is possible to compare them and plot a chart about
how long it takes for achieving some arbitrary level of precisi... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 29 14:31:48 2017
@author: sayala
<NAME> edited 7/28/2017.
Includes passing interpolation parameters to this routine instead of making matlab call each iteration
Also updated to include more than 6 sensors ("numsens"), as we had 9
Interpolation fix... |
<filename>python/cusignal/test/test_filtering.py
# Copyright (c) 2019-2020, NVIDIA CORPORATION.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... |
"""Test functions in the h5io module
These tests copy extensively from deepdish.io to test the io functions that
were modified from the same library. Below is the entire text of deepdish's
BSD-3 license:
---
Copyright (c) 2014, <NAME>
All rights reserved.
Redistribution and use in source and binary forms, with or w... |
<reponame>FurkanCan-eee/Convolutional-Neural-Network
# Packages
import tensorflow as tf
import numpy as np
import scipy.misc
from tensorflow.keras.applications.resnet_v2 import ResNet50V2
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.resnet_v2 import preprocess_input, decode_predi... |
<reponame>kastnerkyle/harmonic_recomposition_workshop
import tensorflow as tf
import numpy as np
from scipy import linalg
from scipy.stats import truncnorm
from scipy.misc import factorial
import tensorflow as tf
from ..core import _get_name
from ..core import get_logger
from ..core import _get_name
from ..core import... |
<reponame>Muhammad-Yunus/Hoax-Classifier-App<gh_stars>1-10
from datetime import datetime
import pandas as pd
import numpy as np
import ast
import os
from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer
from sklearn.preprocessing import normalize
from scipy import sparse
from ml_core.json_util... |
import numpy as np
import scipy
import scipy.optimize
def sound_speed(gamma, pressure, density, dustFrac=0.):
"""
Calculate sound speed, scaled by the dust fraction according to:
.. math::
\widetilde{c}_s = c_s \sqrt{1 - \epsilon}
Where :math:`\epsilon` is the dustFrac
... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 3 00:58:29 2019
Updated
@author: <NAME> and xll
Last updated: Jan 17 2020
Issues seem to arise if tau vector is > 1.5* freq vector, if freq vector is < 100
"""
def cal_Basis(f,t,k=1e4):
import numpy as np
nf = f.size
nt = t.size
Ar = np.... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from absl import app
from collections import Counter
from scipy.signal import lfilter
def _parse_integer(bytes):
int_str = bytes.decode('ASCII')
integers = []
try:
int... |
<reponame>MehdiN/sphere
#!/usr/bin/env python
"""
The algorithms here are partially based on methods described in:
[The Fisher-Bingham Distribution on the Sphere, <NAME>
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 44, No. 1 (1982), pp. 71-80 Published by: Wiley
Article Stable URL: http://ww... |
# -*- coding: utf-8 -*-
from __future__ import print_function, division
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
from torch.autograd import Variable
import torch.backends.cudnn as cudnn
import numpy as np
import torchvision
from torchvision im... |
<filename>mptpy/optimization/operations/substitution.py
""" Interface for applying operations to MPTs.
"""
from sympy.combinatorics.partitions import RGS_enum, RGS_unrank
from mptpy.optimization.operations.operation import Operation
class Substitution(Operation):
""" Parameter deletion operation on MPTs """
... |
<reponame>jaheel/Machine-Learning-Method_Code
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial.distance import pdist, squareform
def get_k_matrix(data, k):
"""
近邻矩阵
@ param data: 样本集
@ param k: 近邻参数
@ return k_dist: 近邻矩阵
"""
dist = pdist(data, 'euclidean') #距离矩阵
d... |
<reponame>gsidsid/ErrorControl
import numpy as np
from scipy.linalg import solve
import random
import binascii
import time
noise_prob = 0.05
def decision(probability):
return random.random() < probability
print(" ")
toControlMessage = raw_input("Enter a message: \n")
binarizedMessage = ' '.join(format(ord(x), '... |
from collections import defaultdict
import numpy as np
from scipy import sparse
from ..indexing import inverse_index_dict
class CatmullClarkSubdiv(object):
def __init__(self, quads):
quads = np.array(quads)
assert quads.shape[1] == 4
self._quads_lo = quads
n_verts = quads.max() +... |
import scipy.signal as sps
import numpy as np
def smoothing(im, ny_nx, sy_sx=(1,1), mask=np.array([]), gk=np.array([]), mirror=False):
"""
This function performs 2D smoothing by convolving a masked image with a kernel.
Parameters
----------
im : 2D array
Image to be smoothed
nx,ny ... |
import scipy
import importlib
from hydroDL.master import basins
from hydroDL.app import waterQuality
from hydroDL import kPath, utils
from hydroDL.model import trainTS
from hydroDL.data import gageII, usgs
from hydroDL.post import axplot, figplot
import torch
import os
import json
import pandas as pd
import numpy as n... |
import unittest
import numpy as np
import scipy.signal
import ibllib.dsp.fourier as ft
from ibllib.dsp import WindowGenerator, rms, rises, falls, fronts, smooth, shift, fit_phase,\
fcn_cosine
class TestDspMisc(unittest.TestCase):
def test_dsp_cosine_func(self):
x = np.linspace(0, 40)
fcn = f... |
import numpy as np
import pandas as pd
import sys
sys.path.append("..")
sys.path.append("../..")
import utils3 as utils
from ParentThermalModel import ParentThermalModel
import yaml
from scipy.optimize import curve_fit
# following model also works as a sklearn model.
# TODO rename a1 and a2 to heating and cooling ... |
import mne
import numpy as np
from src.utils import get_SAflow_bids
from src.neuro import compute_PSD_hilbert, compute_PSD
from src.saflow_params import BIDS_PATH, IMG_DIR, FREQS, FREQS_NAMES, SUBJ_LIST, BLOCS_LIST
from scipy.io import savemat
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add... |
from anndata import AnnData
from typing import Optional
from scipy.sparse import csr_matrix, find, issparse
import pandas as pd
import numpy as np
from .. import logging as logg
from .. import settings
def diffusion(
adata: AnnData,
n_components=10,
knn=30,
alpha=0,
multiscale: bool = True,
n... |
# -*- coding: utf-8 -*-
"""
This module is used for calculations of the orthonormalization matrix for
the boundary wavelets.
The boundary_wavelets.py package is licensed under the MIT "Expat" license.
Copyright (c) 2019: <NAME> and <NAME>.
"""
# ========================================================================... |
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